decision-table-test-design
Derives human-readable manual test cases from a business-rule spec via a decision table: identify conditions and actions, build the full 2^n-column matrix, collapse columns with irrelevant entries, strike infeasible combinations, then emit one test case per remaining column (each feasible column is one coverage item per ISTQB CTFL v4.0 section 4.2.3). A deep single-technique walkthrough rather than a broad multi-lens case matrix; the output is manual step/expected cases rather than parameterized test code, and it covers how cases are derived rather than how a case record is structured. Use when a spec's outcome depends on interacting conditions (pricing, eligibility, discounts, routing rules) rather than the boundaries of a single input.
Install with skills.sh (any agent)
npx skills add testland/qa --skill decision-table-test-designdecision-table-test-design
Overview
Per ISTQB CTFL Syllabus v4.0.1 §4.2.3 (opens in new window), "decision tables are used for testing the implementation of requirements that specify how different combinations of conditions result in different outcomes" and are "an effective way of recording complex logic, such as business rules." This skill walks that derivation end to end: spec in, human-readable manual test cases out (step/expected tables, not code).
All syllabus claims below come from that v4.0.1 PDF (2024-09-15 revision); later references cite it as §4.2.3 without repeating the URL. One worked example (a shipping-fee rule) is carried through every step.
When to use (and when EP/BVA wins)
Use a decision table when the spec is business-rule logic with interacting conditions - the outcome depends on the combination of conditions, not on any single condition alone (pricing, discount stacking, eligibility, approval routing, feature gating). §4.2.3 names a second use: the technique "provides a systematic approach to identify all the combinations of conditions, some of which might otherwise be overlooked" and "helps to find any gaps or contradictions in the requirements", so a reviewer can also run it to check a spec for completeness.
Prefer equivalence partitioning / boundary value analysis instead when a single input's range drives the behavior (e.g. "age must be 18-120"): EP/BVA exercises the edges of one partition; a decision table exercises the cross-product of several conditions. The two compose - derive the rule columns here, then hand each numeric threshold (like the $50 below) to boundary-value-generator for edge values. For a broad first-pass matrix across many lenses rather than one technique in depth, use test-case-ideation-from-story.
Worked example spec (used in every step)
Shipping fee rules. Premium members always ship free (standard or express). Non-members: standard shipping is free for orders of $50 or more, otherwise $5.99; express shipping is a flat $14.99. Express is only offered at checkout for orders of $50 or more (courier minimum).
Step 1 - Identify conditions and actions
Per §4.2.3, "the conditions and the resulting actions of the system are defined. These form the rows of the table. Each column corresponds to a decision rule that defines a unique combination of conditions, along with the associated actions."
Extract from the spec:
| ID | Conditions (Boolean) |
|---|---|
| C1 | Customer is a premium member |
| C2 | Order total is $50 or more |
| C3 | Express shipping selected |
| ID | Actions |
|---|---|
| A1 | Charge $0.00 (free shipping) |
| A2 | Charge $5.99 standard fee |
| A3 | Charge $14.99 express fee |
Guidance: make each condition atomic (one yes/no question) and independently settable by a tester. "Member with a large order" is two conditions, not one. Every distinct outcome in the spec becomes an action row; if an outcome appears in the spec but in no action row, you mis-extracted.
Step 2 - Build the full table (2^n columns)
"A full decision table has enough columns to cover every combination of conditions" (§4.2.3). For n Boolean conditions that is 2^n columns; here 2^3 = 8.
Notation, per the same section: T means the condition is satisfied, F not satisfied, a dash (written - here) means the condition's value "is irrelevant for the action outcome", and N/A means the condition "is infeasible for a given rule". For actions, X means the action should occur and blank means it should not. The syllabus adds that "other notations may also be used."
Fill every column mechanically from the spec:
| R1 | R2 | R3 | R4 | R5 | R6 | R7 | R8 | |
|---|---|---|---|---|---|---|---|---|
| C1 member | T | T | T | T | F | F | F | F |
| C2 total >= $50 | T | T | F | F | T | T | F | F |
| C3 express | T | F | T | F | T | F | T | F |
| A1 free | X | X | ? | X | X | ? | ||
| A2 $5.99 | X | |||||||
| A3 $14.99 | X | ? |
R3 and R7 already smell: the spec says express is only offered at $50 or more, so "express selected on a sub-$50 order" may not be reachable. Mark them ? for now; Step 4 resolves it. Do not skip building the full table: the mechanical cross-product is what surfaces the overlooked combinations §4.2.3 warns about.
Step 3 - Collapse with irrelevant (dash) entries
The table "can also be minimized by merging columns, in which some conditions do not affect the outcome, into a single column" (§4.2.3). (Formal minimization algorithms are explicitly "out of scope of this syllabus"; pairwise inspection is enough at this scale.)
A merge is legal only if every expansion of the dash is feasible and produces identical actions.
Step 4 - Spot infeasible combinations
"The table can be simplified by deleting columns containing infeasible combinations of conditions" (§4.2.3).
Re-read the spec for constraints that make condition combinations unreachable. Here: express is never offered below $50, so C3 = T with C2 = F cannot occur. R3 and R7 are infeasible; delete them. That kills the held merges from Step 3: C2 is not irrelevant in the express columns, because only one of its values is reachable there. A naive R1 + R3 merge would have produced a test case for an impossible state.
Final collapsed table (5 feasible columns):
| P1 | P2 | P3 | P4 | P5 | |
|---|---|---|---|---|---|
| C1 member | T | T | F | F | F |
| C2 total >= $50 | T | - | T | T | F |
| C3 express | T | F | T | F | F |
| A1 free | X | X | X | ||
| A2 $5.99 | X | ||||
| A3 $14.99 | X |
The infeasible columns are not test-less: add one constraint check outside the table that verifies the infeasibility itself holds (the express option is absent from checkout below $50). If that check fails, the table must be rebuilt with R3/R7 feasible.
Step 5 - One test case per remaining column
Per §4.2.3, "the coverage items are the columns containing feasible combinations of conditions", 100% coverage means test cases "exercise all these columns", and "coverage is measured as the number of exercised columns, divided by the total number of feasible columns". Here: 5 feasible columns = 5 coverage items; the 5 cases below = 100% decision table coverage (5/5).
For a dash entry, pick one concrete value (P2 below uses $20; pairing with BVA would add $49.99/$50.00 around the threshold).
| TC ID | Column | Setup | Action | Expected result |
|---|---|---|---|---|
| TC-DT-1 | P1 | Member account; cart total $80.00 | Select express at checkout | Shipping line shows $0.00; order total unchanged |
| TC-DT-2 | P2 | Member account; cart total $20.00 | Select standard at checkout | Shipping line shows $0.00 |
| TC-DT-3 | P3 | Non-member account; cart total $80.00 | Select express at checkout | Shipping line shows $14.99 |
| TC-DT-4 | P4 | Non-member account; cart total $80.00 | Select standard at checkout | Shipping line shows $0.00 |
| TC-DT-5 | P5 | Non-member account; cart total $20.00 | Select standard at checkout | Shipping line shows $5.99 |
| TC-DT-6 | (constraint) | Non-member account; cart total $20.00 | Open shipping options at checkout | Express option is not offered |
Each row expands into a full runnable script (preconditions, per-step expected results, sign-off) via manual-test-script-author; this skill's output is the derivation plus the case table above.
Extended-entry tables and anti-patterns
The limited-entry vs extended-entry table forms (when to collapse correlated numeric conditions into one row) and the technique's anti-patterns table are in references/decision-table-details.md.
Limitations
References
Extended-entry tables and anti-patterns
View source (opens in new window)Extended-entry tables and anti-patterns
Deep reference for decision-table-test-design SKILL.md. Section numbers (§4.2.3) refer to ISTQB CTFL Syllabus v4.0.1, cited in full in the skill's References section.
Limited-entry vs extended-entry tables
Per §4.2.3: "in limited-entry decision tables all the values of the conditions and actions (except for irrelevant or infeasible ones) are shown as Boolean values", while "in extended-entry decision tables some or all the conditions and actions may also take on multiple values (e.g., ranges of numbers, equivalence partitions, discrete values)".
The tables in the skill body are limited-entry. If the spec later adds a tier (orders of $200 or more ship express free for everyone), prefer one extended-entry condition over two correlated Booleans:
| E1 | E2 | E3 | |
|---|---|---|---|
| C1 member | F | F | F |
| C2 order total | < $50 | $50 to $199.99 | >= $200 |
| C3 express | F | T | T |
| Action: fee | $5.99 | $14.99 | $0.00 |
Extended entries keep correlated conditions (total >= $50, total >= $200) in one row, which avoids manufacturing infeasible columns like "total >= $200 but not >= $50".
Anti-patterns
| Anti-pattern | Why it fails | Fix |
|---|---|---|
| Testing only the happy columns | The spec's gaps live in the F-heavy columns; §4.2.3's whole point is the combinations that would otherwise be overlooked | One test case per feasible column; coverage = exercised/feasible columns |
| Skipping infeasible-combination analysis | Naive collapses (R1 + R3 here) produce test cases for unreachable states; testers burn time failing to set them up | Step 4 before finalizing any merge; add a constraint check per deleted column |
| Collapsing before checking actions match | A dash that hides two different outcomes silently deletes a rule | Merge only when every expansion yields identical action rows |
| Tables with many conditions, no reduction | §4.2.3: "the number of rules grows exponentially with the number of conditions" | Per §4.2.3, use "a minimized decision table or a risk-based approach"; or split the rule set per feature |
| Non-atomic conditions ("member with big order") | Column semantics become ambiguous; collapse logic breaks | One yes/no question per condition row (Step 1) |
| No action row for an outcome in the spec | The table cannot reveal the contradiction it was built to find | Re-extract actions until every spec outcome maps to a row |
Related skills
bug-bash-facilitator
Builds a structured bug-bash session - pre-bash kit (charter, test-data prep, environment setup, sign-up sheet), in-bash structure (role rotation across cohorts, shared backlog board, real-time triage), scoring rubric (severity weighting, novelty bonus), and a post-bash same-day wrap-up authored by the facilitator (not a standalone debrief: for post-session writeups without a live bash, use the PROOF debrief in exploratory-testing). Use when a team needs a coordinated multi-tester sweep before a release or after a major change - converts an ad-hoc "everyone test for an hour" into a recorded, comparable session with deliverables.
exploratory-charter-author
Authoring workflow that turns a feature spec, risk area, or bug cluster into a session-based exploratory testing charter per Jonathan and James Bach's SBTM - frames the one-sentence mission, scopes 3-7 areas, picks a 60 / 90 / 120 min time-box, suggests tours, and wires the PROOF debrief deliverables. Per Bach, exploratory testing is "performing tests while learning things that may influence the testing" - the charter sets the mission while leaving exact steps to the tester's judgment. Use when a feature has too many unknowns to script (new feature / refactor blast-radius / bug cluster) and a session-based exploration is the right approach. Authors the charter only: the ready-to-fill charter card, session vocabulary, debrief template, and session review live in the exploratory-testing skill this workflow composes with.
exploratory-testing
Plans and runs time-boxed exploratory testing when tester hours are scarce before a release - one tester with two free 45-minute blocks before code freeze, a high-stakes window such as year-end payroll, or a device and environment the scripted suite never touches. Session-based per the Bachs' SBTM: charters (Explore X with Y to discover Z), 60-90 minute sessions, session sheets with TBS metrics, and the PROOF debrief. Bundles the exploration heuristics as references - Whittaker's seven tours, Kelly's FCC CUTS VIDS, Bach's SFDPOT. Broader than exploratory-charter-author, which writes one charter document: this owns the whole cycle from budgeting the available hours to debriefing what was found. Use when deciding what to explore with the time available, and how to run and record those sessions.
manual-test-script-author
Builds stakeholder-readable scripted manual test cases from a feature spec in four formats: a step-table (preconditions / steps / expected result / actual / pass-fail / notes) for spreadsheet review, a Gherkin Given/When/Then format for BDD-aware teams, a business-language UAT script with acceptance-criteria mapping and contractual sign-off (references/uat-format.md), and a one-line-per-item execution checklist for smoke / on-call / bug-bash / compliance sweeps (references/checklist-format.md). Each script is self-contained (no implicit team knowledge), single-scenario (one happy + N edge per script), and includes the data setup the tester needs without being a developer. Use when a feature can't be (or shouldn't be) fully automated and a human tester needs an executable script or checklist - UAT sign-off rounds, regression baselines, certification testing, deploy smoke checklists, exploratory follow-up scripts.
state-transition-test-design
Derives human-readable manual test cases from stateful behavior: identify states, events, transitions, and guard conditions, draw the state table including invalid (empty-cell) transitions, choose a coverage level (all states, valid transitions / 0-switch, transition pairs / 1-switch per Chow, all transitions including invalid ones), then derive one test case per coverage item as an event sequence with per-step expected states (ISTQB CTFL v4.0 section 4.2.4). A deep single-technique walkthrough rather than a broad multi-lens case matrix; the output is manual step/expected cases rather than parameterized test code, and it covers how cases are derived rather than how a case record is structured. Use for lifecycle entities (accounts, orders, subscriptions), workflows, and UI wizards where the response to an event depends on the current state.